DETECTION AND QUANTITATION OF THE CBF-BETA MYH11 TRANSCRIPTS ASSOCIATED WITH THE INV(16) IN PRESENTATION AND FOLLOW-UP SAMPLES FROM PATIENTS WITH AML/

Citation
Pas. Evans et al., DETECTION AND QUANTITATION OF THE CBF-BETA MYH11 TRANSCRIPTS ASSOCIATED WITH THE INV(16) IN PRESENTATION AND FOLLOW-UP SAMPLES FROM PATIENTS WITH AML/, Leukemia, 11(3), 1997, pp. 364-369
Citations number
19
Categorie Soggetti
Hematology,Oncology
Journal title
ISSN journal
08876924
Volume
11
Issue
3
Year of publication
1997
Pages
364 - 369
Database
ISI
SICI code
0887-6924(1997)11:3<364:DAQOTC>2.0.ZU;2-C
Abstract
We have developed a competitor-based RT-PCR technique which will detec t and quantitate the CBF beta/MYH11 transcripts associated with inv(16 )(q22;p13) and have used it to study presentation and follow-up sample s of acute myeloid leukaemia (AML). The levels of the leukaemia-specif ic transcripts are expressed as a ratio to a ubiquitously expressed mR NA species (Abl) which controls for RNA degradation. This technique ha s been applied to 75 consecutive patients presenting with either de no vo AML or tMDS; 6/75 patients analysed were positive for the inv(16), all were confirmed by conventional cytogenetics. The inv(16) has a str ong association with M4Eo, but we found only 2/6-positive patients to have this diagnosis (two patients with M2, one patient M1 and one pati ent had MDS). At presentation the levels of CBF beta/MYH11 transcripts were 0.1-10/Abl transcript (mean 3.3/Abl transcript). Seventeen follo w-up samples were available on 5/6 of these patients, and on two furth er patients in whom stored material was available. Following the first cycle of chemotherapy the level of transcripts was at least 10(-2) lo wer (0.1-10 x 10(-2)/abl transcript) than their presentation sample. S ubsequent samples on these patients when in remission gave transcript levels in the range (1.0 x 10(-4)-2 x 10(-3)/abl transcript), and thre e long-term followup samples were negative. We have developed a quanti tative test which opens the possibility of predicting relapse by detec ting changes in the numbers of leukaemia-specific transcripts.